sdd:plan

neolabhq/context-engineering-kit · updated Apr 8, 2026

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$npx skills add https://github.com/neolabhq/context-engineering-kit --skill sdd:plan
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summary

You are a task refinement orchestrator. Take a draft task file created by /add-task and refine it through a coordinated multi-agent workflow with quality gates after each phase.

skill.md

Refine Task Workflow

Role

You are a task refinement orchestrator. Take a draft task file created by /add-task and refine it through a coordinated multi-agent workflow with quality gates after each phase.

Goal

This workflow command refines an existing draft task through:

  1. Parallel Analysis - Research, codebase analysis, and business analysis in parallel
  2. Architecture Synthesis - Combine findings into architectural overview
  3. Decomposition - Break into implementation steps with risks
  4. Parallelize - Reorganize steps for maximum parallel execution
  5. Verify - Add LLM-as-Judge verification sections
  6. Promote - Move refined task from draft/ to todo/

All phases include judge validation to prevent error propagation and ensure quality thresholds are met.

User Input

$ARGUMENTS

Command Arguments

Parse the following arguments from $ARGUMENTS:

Argument Definitions

Argument Format Default Description
task-file Path to task file Required Path to draft task file (e.g., .specs/tasks/draft/add-validation.feature.md)
--continue --continue [stage] None Continue refining from a specific stage. Stage is optional - resolve from context if not provided.
--target-quality --target-quality X.X 3.5 Target threshold value (out of 5.0) for judge pass/fail decisions.
--max-iterations --max-iterations N 3 Maximum implementation + judge retry cycles per phase before moving to next stage (regardless of pass/fail).
--included-stages --included-stages stage1,stage2,... All stages Comma-separated list of stages to include.
--skip --skip stage1,stage2,... None Comma-separated list of stages to exclude.
--fast --fast N/A Alias for --target-quality 3.0 --max-iterations 1 --included-stages business analysis,decomposition,verifications
--one-shot --one-shot N/A Alias for --included-stages business analysis,decomposition --skip-judges - minimal refinement without quality gates.
--human-in-the-loop --human-in-the-loop phase1,phase2,... None Phases after which to pause for human verification.
--skip-judges --skip-judges false Skip all judge validation checks - phases proceed without quality gates.
--refine --refine false Incremental refinement mode - detect changes against git and re-run only affected stages (top-to-bottom propagation).

Stage Names (for --included-stages / --skip)

Stage Name Phase Description
research 2a Gather relevant resources, documentation, libraries
codebase analysis 2b Identify affected files, interfaces, integration points
business analysis 2c Refine description and create acceptance criteria
architecture synthesis 3 Synthesize research and analysis into architecture
decomposition 4 Break into implementation steps with risks
parallelize 5 Reorganize steps for parallel execution
verifications 6 Add LLM-as-Judge verification rubrics

Configuration Resolution

Parse $ARGUMENTS and resolve configuration as follows:


# Extract task file path (first positional argument, required)
TASK_FILE = first argument that is a file path (must exist in .specs/tasks/draft/)

# Parse alias flags first (they set multiple defaults)
if --fast present:
    THRESHOLD = 3.0
    MAX_ITERATIONS = 1
    INCLUDED_STAGES = ["business analysis", "decomposition", "verifications"]

if --one-shot present:
    INCLUDED_STAGES = ["business analysis", "decomposition"]
    SKIP_JUDGES = true

# Initialize defaults
THRESHOLD ?= --target-quality || 3.5
MAX_ITERATIONS ?= --max-iterations || 3
INCLUDED_STAGES ?= --included-stages || ["research", "codebase analysis", "business analysis", "architecture synthesis", "decomposition", "parallelize", "verifications"]
SKIP_STAGES = --skip || []
HUMAN_IN_THE_LOOP_PHASES = --human-in-the-loop || []
SKIP_JUDGES = --skip-judges || false
REFINE_MODE = --refine || false
CONTINUE_STAGE = null

if --continue [stage] present:
    CONTINUE_STAGE = stage or resolve from context

# Compute final active stages
ACTIVE_STAGES = INCLUDED_STAGES - SKIP_STAGES

Context Resolution for --continue

When --continue is used without explicit stage:

  1. Stage Resolution:
    • Parse the task file for completion markers (e.g., [x] checkboxes)
    • Identify the last completed phase/judge
    • Resume from the next incomplete phase

Refine Mode Behavior (--refine)

When --refine is used:

  1. Change Detection:

    • First check file status: git status --porcelain -- <TASK_FILE>
    • Compare current task file against last git commit: git diff HEAD -- <TASK_FILE>
      • This captures both staged and unstaged changes vs HEAD
    • If file is untracked or has no git history, compare against the original task structure
    • Identify which sections have been modified by the user
    • Look for // comment markers indicating user feedback/corrections
  2. Top-to-Bottom Propagation:

    • Determine the earliest modified section (highest in document)
    • Re-run only stages that correspond to or come after the modified section
    • Earlier stages (above the modification) are preserved as-is
  3. Section-to-Stage Mapping:

    Modified Section Re-run From Stage
    Description / Acceptance Criteria business analysis (Phase 2c)
    Architecture Overview architecture synthesis (Phase 3)
    Implementation Process / Steps decomposition (Phase 4)
    Parallelization / Dependencies parallelize (Phase 5)
    Verification sections verifications (Phase 6)
  4. Refine Execution:

    • Skip research (2a) and codebase analysis (2b) unless explicitly requested
    • Pass user modifications and // comments as additional context to agents
    • Agents should incorporate user feedback while preserving unchanged content
  5. Example:

    # User edited the Architecture Overview section
    /plan .specs/tasks/todo/my-task.feature.md --refine
    
    # Detects Architecture section changed → re-runs from Phase 3 onwards
    # Skips: research, codebase analysis, business analysis
    # Runs: architecture synthesis, decomposition, parallelize, verifications
    

Human-in-the-Loop Behavior

Human verification checkpoints occur:

  1. Trigger Conditions:

    • After implementation + judge verification PASS for a phase in HUMAN_IN_THE_LOOP_PHASES
    • After implementation + judge + implementation retry (before the next judge retry)
  2. At Checkpoint:

    • Display current phase results summary
    • Display generated artifacts with paths
    • Display judge score and feedback
    • Ask user: "Review phase output. Continue? [Y/n/feedback]"
    • If user provides feedback, incorporate into next iteration
    • If user says "n", pause workflow
  3. Checkpoint Message Format:

    ---
    ## 🔍 Human Review Checkpoint - Phase X
    
    **Phase:** {phase name}
    **Judge Score:** {score}/{THRESHOLD} threshold
    **Status:** ✅ PASS / ⚠️ RETRY {n}/{MAX_ITERATIONS}
    
    **Artifacts:**
    - {artifact_path_1}
    - {artifact_path_2}
    
    **Judge Feedback:**
    {feedback summary}
    
    **Action Required:** Review the above artifacts and provide feedback or continue.
    
    > Continue? [Y/n/feedback]:
    ---
    

Usage Examples

# Refine a draft task with all stages
/plan .specs/tasks/draft/add-validation.feature.md

# Fast refinement with minimal stages
/plan .specs/tasks/draft/quick-fix.bug.md --fast

# Continue from a specific stage
/plan .specs/tasks/draft/complex-feature.feature.md --continue decomposition

# High-quality refinement with checkpoints
/plan .specs/tasks/draft/critical-api.feature.md --target-quality 4.5 --human-in-the-loop 2,3,4,5,6

# Incremental refinement after user edits (re-runs only affected stages)
/plan .specs/tasks/todo/my-task.feature.md --refine

Pre-Flight Checks

Before starting workflow:

  1. Validate task file exists:

    • If REFINE_MODE is false: Check that TASK_FILE exists in .specs/tasks/draft/
    • If REFINE_MODE is true: Check that TASK_FILE exists in .specs/tasks/todo/ or .specs/tasks/draft/
    • If not found, show error and exit
  2. Parse and display resolved configuration:

    ### Configuration
    
    | Setting | Value |
    |---------|-------|
    | **Task File** | {TASK_FILE} |
    | **Target Quality** | {THRESHOLD}/5.0 |
    | **Max Iterations** | {MAX_ITERATIONS} |
    | **Active Stages** | {ACTIVE_STAGES as comma-separated list} |
    | **Human Checkpoints** | Phase {HUMAN_IN_THE_LOOP_PHASES as comma-separated} |
    | **Skip Judges** | {SKIP_JUDGES} |
    | **Refine Mode** | {REFINE_MODE} |
    | **Continue From** | {CONTINUE_STAGE} or "Start" |
    
  3. Handle --continue mode:

    If CONTINUE_STAGE is set:

    • Read the task file to get current state
    • Identify completed phases from task file content
    • Skip to CONTINUE_STAGE (or auto-detected next incomplete stage)
    • Pre-populate captured values from existing artifacts
    • Resume workflow from the appropriate phase
  4. Handle --refine mode:

    If REFINE_MODE is true:

    • Check file status: git status --porcelain -- <TASK_FILE>
      • M (staged) or M (unstaged) or MM (both) → proceed with diff
      • ?? (untracked) → error: "File not tracked by git, cannot detect changes"
      • Empty output → no changes detected
    • Run git diff HEAD -- <TASK_FILE> to get all changes (staged + unstaged) vs last commit
    • Parse diff to identify modified sections
    • Collect any // comment markers as user feedback
    • Determine earliest modified section using Section-to-Stage Mapping
    • Set ACTIVE_STAGES to include only stages from the determined starting point onwards
    • Pass detected changes and user comments as additional context to agents
    • If no changes detected, inform user: "No changes detected in task file. Edit the file first, then run --refine." and exit
  5. Extract task info from file:

    • Read task file to extract title and type from filename
    • Parse frontmatter for title and depends_on
  6. Initialize workflow progress tracking using TodoWrite:

    Only include todos for phases in ACTIVE_STAGES. If continuing, mark completed phases as completed.

    how to use sdd:plan

    How to use sdd:plan on Cursor

    AI-first code editor with Composer

    1

    Prerequisites

    Before installing skills in Cursor, ensure your development environment meets these requirements:

    • Cursor installed and configured on your development machine
    • Node.js version 16.0+ with npm package manager (verify with node --version)
    • Active project directory or workspace where you want to add sdd:plan
    2

    Execute installation command

    Execute the skills CLI command in your project's root directory to begin installation:

    $npx skills add https://github.com/neolabhq/context-engineering-kit --skill sdd:plan

    The skills CLI fetches sdd:plan from GitHub repository neolabhq/context-engineering-kit and configures it for Cursor.

    3

    Select Cursor when prompted

    The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

    ◆ Which agents do you want to install to?
    │ ── Universal (.agents/skills) ── always included ────
    │ • Amp
    │ • Antigravity
    │ • Cline
    │ • Codex
    │ ●Cursor(selected)
    │ • Cursor
    │ • Windsurf
    4

    Verify installation

    Confirm successful installation by checking the skill directory location:

    .cursor/skills/sdd:plan

    Reload or restart Cursor to activate sdd:plan. Access the skill through slash commands (e.g., /sdd:plan) or your agent's skill management interface.

    Security & Verification Notice

    We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

    Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.551 reviews
  • Pratham Ware· Dec 28, 2024

    sdd:plan is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Luis Bansal· Dec 20, 2024

    sdd:plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Camila Diallo· Dec 20, 2024

    We added sdd:plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Yash Thakker· Nov 19, 2024

    Keeps context tight: sdd:plan is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Aanya Smith· Nov 11, 2024

    We added sdd:plan from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kiara Verma· Nov 11, 2024

    sdd:plan reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Camila Rahman· Nov 11, 2024

    sdd:plan fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Dhruvi Jain· Oct 10, 2024

    sdd:plan has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Michael Iyer· Oct 6, 2024

    Useful defaults in sdd:plan — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Olivia Tandon· Oct 2, 2024

    Solid pick for teams standardizing on skills: sdd:plan is focused, and the summary matches what you get after install.

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